testcheck-temp
v1.0.0-rc.2-temp2
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Property testing for JavaScript
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TestCheck-temp.js
note: This is a temporary package of testcheck. To install original pacakage please refer to https://github.com/leebyron/testcheck-js.
Generative property testing for JavaScript.
TestCheck.js
is a library for generative testing of program properties,
ala QuickCheck.
By providing a specification of the JavaScript program in the form of properties, the properties can be tested to remain true for a large number of randomly generated cases. In the case of a test failure, the smallest possible failing test case is found.
Getting started
Or using npm
npm install --save-dev testcheck-temp
Then require it into your testing environment and start testing.
const { check, gen, property } = require('testcheck-temp');
const result = check(
property(
gen.int,
x => x - x === 0
)
)
Have a favorite test framework?
TestCheck.js
is a testing utility and not a complete test-running framework. It
doesn't replace test frameworks like AVA, Jasmine, or Mocha.
If you use AVA then check out ava-check, a testcheck AVA plugin.
const test = require('ava')
const { check, gen } = require('ava-check')
test('addition is commutative', check(gen.int, gen.int, (t, numA, numB) => {
t.true(numA + numB === numB + numA)
}))
If you use Jasmine or Jest then check out jasmine-check, a testcheck Jasmine (or Jest) plugin.
require('jasmine-check').install()
describe('Maths', () => {
check.it('addition is commutative', gen.int, gen.int, (numA, numB) => {
expect(numA + numB).toEqual(numB + numA)
})
})
If you use Mocha then check out mocha-testcheck, a testcheck Mocha plugin.
require('mocha-testcheck').install();
const { expect } = require('chai');
describe('Maths', () => {
check.it('addition is commutative', gen.int, gen.int, (numA, numB) => {
expect(numA + numB).to.equal(numB + numA)
})
})
If you use Tape then check out tape-check, a testcheck Tape plugin.
const test = require('tape')
const { check, gen } = require('tape-check')
test('addition is commutative', check(gen.int, gen.int, (t, numA, numB) => {
t.plan(1)
t.equal(numA + numB, numB + numA)
}));
Type definitions
This module includes type definitions for Flow type and Typescript. Simply require or import this module and enjoy type suggestions and corrections.
Using TestCheck.js
See the complete API documentation for all available generators and utilities, or the Walkthrough Guide for a more thorough walkthrough.
Try it! Open the developer console while viewing the docs to follow along with the examples below.
Defining properties
A property is simply a function which is expected to always return true, we might also call these properties "assumptions" or "expectations".
For example, say we wanted to test the assumption that any number subtracted
from itself will be 0
, we could define this property as:
function (x) {
return x - x === 0
}
Or as another example, let's determine that sorting an array is stable and idempotent, which is to say that sorting a sorted array shouldn't do anything. We could write:
function (arr) {
var arrCopy = arr.slice()
return deepEqual(arrCopy.sort(), arr.sort().sort())
}
That's really it! The only thing special about this property function is that it is pure, e.g. it relies only on the provided arguments to determine its return value (no other reading or writing!).
If you can start to describe your program in terms of its properties, then
testcheck
can test them for you.
Generating test cases
Once we've defined some properties, we generate test cases for each properties by describing the types of values for each argument.
For testing our first property, we need numbers:
gen.int
For the second, we need arrays of numbers
gen.array(gen.int)
There are a wide variety of value generators, we've only scratched the surface.
We can generate random JSON with gen.JSON
, pick amongst a set of values with
gen.returnOneOf
, nested arrays with ints gen.nested(gen.array, gen.int)
and
much more. You can even define your own generators with generator.then()
,
and gen.sized
.
Checking the properties
Finally, we check our properties using our test case generator (in this case, up to 1000 different tests before concluding).
const result = check(
property(
// the arguments generator
gen.int,
// the property function to test
x => x - x === 0
),
{ numTests: 1000 }
)
check
runs through random cases looking for failure, and when it doesn't find
any failures, it returns:
{ result: true, numTests: 1000, seed: 1406779597155 }
Smallest failing test
Let's try another property: the sum of two integers is the same or larger than either of the integers alone.
check(
property(
gen.int, gen.int,
(a, b) => a + b >= a && a + b >= b
)
)
check
runs through random cases again. This time it found a failing case, so
it returns:
{ result: false,
failingSize: 2,
numTests: 3,
fail: [ 2, -1 ],
shrunk:
{ totalNodesVisited: 2,
depth: 1,
result: false,
smallest: [ 0, -1 ] } }
Something is wrong. Either:
- Our assumption is wrong (e.g. bug in our software).
- The test code is wrong.
- The generated test data is too broad.
In this case, our problem is that our generated data is too broad for our assumption. What's going on?
We can see that the fail
case 2, -1
would in fact not be correct, but it
might not be immediately clear why. This is where test case shrinking comes in
handy. The shrunk
key provides information about the shrinking process and
most importantly, the smallest
values that still fail: 0, -1
.
We forgot about an edge case! If one of the integers is negative, then the sum will not be larger. This shrunken test case illustrated this much better than the original failing test did. Now we know that we can either improve our property or make the test data more specific:
check(property(
gen.posInt, gen.posInt,
(a, b) => a + b >= a && a + b >= b
));
With our correction, our property passes all tests.
Thinking in random distributions
It's important to remember that your test is only as good as the data being
provided. While testcheck
provides tools to generate random data, thinking
about what that data looks like may help you write better tests. Also, because
the data generated is random, a test may pass which simply failed to uncover
a corner case.
"Testing shows the presence, not the absence of bugs"
— Dijkstra, 1969
Sampling Test Data
Visualizing the data check
generates may help diagnose the quality of a test.
Use sample
and sampleOne
to get a look at what a generator produces:
const { gen, sample, sampleOne } = require('testcheck')
sample(gen.int)
// [ 0, 0, 2, -1, 3, 5, -4, 0, 3, 5 ]
sampleOne(gen.int)
// -23
The Size of Test Data
Test data generators have an implicit size
property, which could be used to
determine the maximum value for a generated integer or the max length of a
generated array. testcheck
begins by generating small test cases and gradually
increases the size.
So if you wish to test very large numbers or extremely long arrays, running
check
the default 100 times with maxSize of 200, you may not get what
you expect.
Data relationships
Let's test an assumption that should clearly be wrong: a string split by another string always returns an array of length 1.
check(property(
gen.asciiString.notEmpty(), gen.asciiString.notEmpty(),
(str, separator) => str.split(separator).length === 1
))
Unless you got lucky, you probably saw this check pass. This is because we're
testing for a relationship between these strings. If separator
is not found
in str
, then this test passes. The second unrelated random string is very
unlikely to be found within the first random string.
We could change the test to be aware of this relationship such that the
separator
is always contained within the str
by using then()
.
check(property(
gen.asciiString.notEmpty().then(str =>
[ str, gen.substring(str).notEmpty() ]),
([ str, separator ]) => str.split(separator).length === 1
))
Now separator
is a random substring of str
and the test fails with the
smallest failing arguments: [ ' ', ' ' ]
.
We can test this example out ourselves, with the value ' '
generated for both
str
and separator
, we can run ' '.split(' ').length
to see that we in
fact get 2
, not 1
.
License
Copyright 2014-Present Lee Byron
TestCheck.js is distributed under the BSD-3-Clause license.
Atop the shoulders of giants
TestCheck.js
is based on Clojure's test.check
which is inspired by Haskell's QuickCheck. Many gracious thanks goes to all of the brilliance and hard work enabling this project to exist.
Clojure's test.check is Copyright Rich Hickey, Reid Draper and contributors and is distributed under the Eclipse Public License.